| Title: | OS13-9 A Study of YOLO Algorithm for Target Detection |
|---|---|
| Publication: | ICAROB2021 |
| Volume: | 26 |
| Pages: | 622-625 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2021.OS13-9 |
| Author(s): | Haokang Wen, Fengzhi Dai, Yasheng Yuan |
| Publication Date: | January 21, 2021 |
| Keywords: | target detection, YOLOv5, deep learning, computer vision technology |
| Abstract: | With the development of deep learning, target detection has become one of the research directions of many scholars. As one of the more mature algorithms, the YOLO series of algorithms have been widely used in real life. Combining the development history of the YOLO algorithm, this article focuses on the main framework and main content of the current latest YOLOv5 algorithm, and uses the YOLOv5 model to identify and detect footballs. This article evaluates its detection effect. The test results show that YOLOv5 has a wider application meaning in real life. |
| PDF File: | https://alife-robotics.co.jp/members2021/icarob/data/html/data/OS/OS13/OS13-9.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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